What are the determinants of variation in caretaker satisfaction with sick child consultations? A cross-sectional analysis in five low-income and middle-income countries

Objectives The objective of this study was to explore determinants of variation in overall caretaker satisfaction with curative care for sick children under the age of 5 in five low-income and middle-income countries. Design A pooled cross-sectional analysis was conducted using data from the Service Provision Assessment. Setting We used data collected in five countries (Afghanistan, Democratic Republic of the Congo, Haiti, Malawi and Tanzania) between 2013 and 2018. Participants Respondents were 13 149 caretakers of children under the age of 5 who consulted for a sick child visit. Primary outcomes measured The outcome variable was whether the child’s caretaker was very satisfied versus more or less satisfied or not satisfied overall. Predictors pertained to child and caretaker characteristics, health system foundations and process of care (eg, care competence, user experience). Two-level logistic regression models were used to assess the extent to which these categories of variables explained variation in satisfaction. The main analyses used pooled data; country-level analyses were also performed. Results Process of care, including user experience, explained the largest proportion of variance in caretaker satisfaction (13.8%), compared with child and caretaker characteristics (0.9%) and health system foundations (3.8%). The odds of being very satisfied were lower for caretakers who were not given adequate explanation (OR: 0.56, 95% CI 0.46 to 0.67), who had a problem with medication availability (OR: 0.31, 95% CI 0.27 to 0.35) or who encountered a problem with the cost of services (OR: 0.57, 95% CI 0.48 to 0.66). The final model explained only 21.8% of the total variance. Country-level analyses showed differences in variance explained and in associations with predictors. Conclusions Better process of care, especially user experience, should be prioritised for its benefit regarding caretaker satisfaction. Unmeasured factors explained the majority of variation in caretaker satisfaction and should be explored in future studies.


BACKGROUND
User satisfaction is an important dimension of high-quality health systems. 1 It reflects the ultimate judgement of the consumer and influences decisions on when and where to seek care. 1 Consequently, user satisfaction measures are increasingly used to evaluate the performance of healthcare systems, improve accountability and provide financial incentives to healthcare staff.The results of user satisfaction surveys are also used to help managers and healthcare providers identify service factors needing improvement. 2owever, whether and to what extent user satisfaction measures are appropriate to evaluate health systems depends on the extent to which they are influenced by health system versus other factors.Studies have shown that user satisfaction is a complex and multidimensional concept with numerous determining factors.Batbaatar et al 2 reported that user satisfaction is influenced by technical

STRENGTHS AND LIMITATIONS OF THIS STUDY
⇒ This is the first multicountry analysis to examine the determinants of variation in caretaker satisfaction with healthcare services for sick children under the age of 5 in low-income and middle-income countries (LMICs).⇒ The study has the advantage of combining multiple sources of data (facility audits, health provider interviews and exit interviews with caretakers).⇒ Novel evidence shows that the process of care, including the technical quality of care and the caretaker experience, explains the largest proportion of variance in caretaker satisfaction with sick childcare across five LMICs.⇒ The satisfaction rates reported by caretakers were generally high, possibly due to desirability bias in participants' responses during interviews, low patient expectations and behaviours during the audits.
Open access care, interpersonal care, physical environment, access, organisational characteristics, continuity of care and outcome of care.Focusing on child health, McCormick et al 3 identified the health status of the child, sociodemographic characteristics and history of treatment as predictors of parental satisfaction in the USA.However, these analyses have not paid much attention to broader factors (eg, facility characteristics, country-level characteristics) that may influence user satisfaction.
Understanding the relative contributions of different types of factors to explaining variation in user satisfaction is useful to better interpret and use results from user satisfaction surveys for quality improvement.However, few studies have examined how much variation is explained by determinants of user satisfaction in various countries.One study used data from 21 European Union countries to examine variation in user satisfaction with the health system. 4Those authors found that all factors taken into account in their model, such as patient expectations, health status and personality, explained only 17.5% of the observed variation in user satisfaction, of which 10.4% was explained by user experience with system responsiveness. 4hey concluded that, contrary to published reports, user experience accounts for only a small fraction of variation in user satisfaction with the healthcare system.However, the proportion of variance in user satisfaction explained by health system and non-health system factors in lowincome and middle-income countries (LMICs) remains unclear.Most evidence on this issue was derived in highincome countries.
The objectives of our study were twofold: (1) to assess the proportion of variance in caretaker overall satisfaction explained by factors related to child and caretaker characteristics, health system foundations, and process of care; (2) to identify variables associated with caretaker overall satisfaction in five LMICs.

Study setting
Table 1 presents the demographic characteristics and healthcare situations in the five countries included in this study.All of these countries are characterised by high rates of neonatal mortality.Democratic Republic of the Congo (DRC) had the highest mortality rate for children under the age of 5 per 1000 live births (58) and the lowest health spending per capita (51 PPP$).In contrast, Malawi had the lowest mortality rate for children under the age of 5 (39) and the second lowest value for health spending per capita (82 PPP$).

Data source and sampling
The data were obtained from Service Provision Assessment (SPA) surveys.SPA surveys are conducted by the Demographic and Health Survey Program of United States Agency for International Development, with a national statistics agency in the countries surveyed to measure the capacity of health systems in LMICs.6][7][8][9] For the SPA survey, facilities are selected from a comprehensive list of health facilities in each country, categorised by facility type, managing authority and region; a nationally representative sample of health facilities is selected.A description of the methodology used for SPA surveys is available online. 10 We limited our study population to the most recent SPA surveys that included a question on user satisfaction with consultation for sick children under the age of 5 in five countries: Afghanistan (2018), Democratic Republic of  All caretakers who sought care for a sick child consultation in hospitals or primary healthcare facilities were included in our study without any specific exclusion criteria.We used data from four separate modules: facility audits, health provider interviews, observation of protocols for sick child care and exit interviews with caretakers.Facility audits collected data on available human resources, basic amenities and availability of essential equipment, supplies and medicines.A sample of health providers was selected from the facility roster to be interviewed and observed.Trained enumerators observed clinical visits to assess adherence to clinical guidelines during consultations for sick children.The caretakers (eg, parents, grandparents) of children observed during the consultations completed an exit interview regarding their level of satisfaction with the services received, problems encountered and demographic characteristics.

Data management and quality control
2][13][14][15] The interviewers were supposed to review the data and enter it in tablets.The data files were transferred to a supervisor who oversaw the data collection process.When supervisors noted missing information or errors, they sent the data back to the interviewer for revision.Then, the data were sent to a central office via the Internet.In the central office, data processors detected inconsistencies and gave feedback to the team in the field to resolve the problems.For tracking of systematic errors arising from each interviewer, field check tables were run.[13][14][15] Framework To conceptualise our analyses, we adapted the High Quality Health Systems framework from the Lancet Global Health Commission. 1 As shown in figure 1, this framework comprises three key domains: foundations, process of care and quality impacts. 1 Health system foundations include the population and their health needs, health sector governance, care delivery platforms, workforce skills and tools such as medicines and equipment.Process of care is composed of two subdomains: competent care and user experience.Competent care refers to systematic assessment, correct diagnosis, appropriate treatment, counselling, prevention and detection.Positive user experience refers to respect, autonomy, clear communication, short wait times, patient affordability and ease of use.Caretaker satisfaction, our outcome of interest, is a quality impact measure that contributes to confidence in the system and willingness to use healthcare.

Outcome variable
The outcome variable is caretaker satisfaction, extracted from the exit interview module.The following question was used to elicit caretaker satisfaction regarding the sick child consultation: "In general, which of the following statements best describes your opinion of the services you either received or were provided at this facility today?Very satisfied, more or less satisfied, or not satisfied."Based on the low levels of dissatisfaction, we created a binary variable of satisfaction equal to 1 if the caretaker was very satisfied and 0 otherwise (ie, if the caretaker was more or less satisfied, or not satisfied).

Predictor variables
2][3][4] Child characteristics included gender (male or female), age (12 months or less, 13-59 months and age not specified), and severity of symptoms, constructed by summing the reasons the caretaker identified for bringing in the child, including cough, diarrhoea, fever, vomiting, problem with feeding, convulsions, excessive sleepiness or other symptoms (range: 1-8).Caretaker characteristics included age (≤19, 20-35, ≥36 years and age not specified) and education level (none, primary, secondary, tertiary or higher).

Open access
To characterise the facilities, we examined the types of management authorities (public, private not for profit, private for profit) and whether providers received a regular salary supplement.Facility types categorised into hospitals, health centres or clinics, health posts or dispensaries, and urban setting (vs rural) were included.To characterise the workforce, providers were separated into three categories: physicians/clinical officers/assistant medical officers; nurses/midwives; and aides/assistants.Other provider characteristics included gender and years since graduation (as a proxy for experience).To characterise the facilities' tools, we drew on data from facility audits to calculate a service readiness score for preventive and curative care regarding sick child health based on the WHO Service Availability and Readiness Assessment guidelines. 16The overall score was calculated by averaging all items in four domains: staff and training, equipment, diagnostics, and medicines and commodities.The original scores ranged between 0 and 1 but were multiplied by 10 to facilitate interpretation (0-10).Online supplemental table 1 presents the full list of indicators used.
We assessed the technical quality of sick child consultations by investigating the degree to which the provider adhered to clinical guidelines during the consultation observation. 17 18The technical quality score was calculated as the percentage of clinically recommended tasks performed in four domains: patient history taking, physical exam, drug administration and immunisation, and client education and counselling.We also multiplied the score by 10 to facilitate interpretation.The items included for technical quality indicators for sick child care are presented in the supplementary file (online supplemental tables 2,3).
Caretakers' perceptions of their experience during the visit were examined through exit interviews by asking whether they had encountered problems that day related to: (1) days or hours of service at this facility (ie, when it opened and closed); (2) wait time to see a provider; (3) facility cleanliness; (4) how staff treated them; (5) ability to discuss problems or concerns about the health issue; (6) amount of explanation received about the problem or treatment; (7) medication; and (8) cost of services or treatments.For each of these, responses were scored as the number of problems encountered.We included the country variable as a proxy for country-level outer context.

Statistical analysis
We performed a complete case analysis, which yielded a total of 13 149 sick child visits across 3421 facilities for the sample in the 5 countries.For variables with the most missing data (eg, child age, caretaker age), we added the value 'not specified' to be able to include the cases in the analysis.Less than 5% of the sample had missing data, in total.
We calculated descriptive statistics for all variables of interest, presenting the proportions for categorical variables and mean and SD for continuous covariates.These descriptive analyses incorporated survey sampling weights for patients and facilities.
For the main analyses, we performed a two-level logistic regression analysis based on pooled data from the five countries, where level 1 was the consultation and level 2 was the facility.This provided variance estimates while accounting for clustering effect at the facility level.The following general structure was used: where Y (caretaker satisfaction) and X (representing a vector of independent variables) were each assumed to follow a two-level data structure, with both fixed-effect (β 0 , β • X ij ) and random-effect parameters ( u 0j ).The random-effect parameter ( u 0j ) was assumed to follow a normal distribution, with mean of 0 and variances of u 0j ~ N (0, σ 2 u 0 .We confirmed the linearity between the four continuous independent variables and log-odds of the outcome using the Box-Tidwell test. Four models were estimated based on the general modelling structure outlined above, by incrementally adding blocks of covariates following our conceptual framework (see online supplemental table 4) in the supplementary file for details on the modelling strategy).M0 was a null/unadjusted model with an intercept term in the fixed part of the model.M1 added child and caretaker characteristics.M2 built on the previous model to include variables related to health system foundations.M3 added variables related to the process of care.For the analyses with the pooled data, M4 included the country as a variable.
We applied Snijders and Bosker's method to measure the explained proportion of variance in caretaker satisfaction for the logistic multilevel model (details are provided in online supplemental box of the online supplemental file). 19Since logistic regression models do not have a level 1 residual term, unexplained variance at the consultation level was estimated as π 2 /3 ≈ 3.29 based on the method summarised by Goldstein et al. 8 When considering only the unexplained part of the total variance, the proportion attributed to the health facilities level (called residual intraclass correlation) was calculated.
We also performed country-stratified analyses to examine whether the results were country specific.All analyses were conducted in Stata V. 16.0 (StataCorp).

Patient and public involvement statement
Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination of this research.

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Open access and lowest in Afghanistan (62%).Approximately 68% of caretakers had primary education level or less.Of the providers, 34% were female, and 58% were qualified as doctors or advance practice clinicians.The majority of facilities were health centres (52%) and public (63%).The mean scores for technical quality of care observed were quite low (3.1).Because data in Afghanistan only cover urban areas, the percentage of highly qualified providers, hospitals and private for-profit facilities was notably higher than in the other countries (table 2).

Total variance explained
Figure 2 shows the percentage of variance explained in each model.Variance explained in the fully adjusted model with the combined data from five countries was 21.8%.However, it varied significantly across countries, ranging from 9.0% in DRC to 51.7% in Afghanistan.Factors related to patient and caretaker characteristics only explained 0.9% of the total variance (0.8% in Tanzania~4.3% in Afghanistan).The explained variance increased by 3.8% when variables related to health system foundations, such as facility and provider characteristics, were included (0.9% in Malawi~10.8%Afghanistan).The largest percentage of the total variance was explained by process of care in both the pooled and country-stratified analyses.When process of care variables were added, the explained variance increased by 13.8% in the pooled analyses.Variance explained by process of care was notably higher in Afghanistan and Tanzania (36.6% and 24.2%, respectively) than in the other countries (5.8% in DRC~10.4% in Malawi).

Determinants of caretaker satisfaction
Figure 3 shows the results of the final model's fixed part based on the pooled data from the five countries.More severe symptoms of the child (OR: 0.94, 95% CI 0.91 to 0.98) and higher education of caretakers (OR: 0.78 and 0.53, 95% CI 0.66 to 0.93 and 0.40 to 0.69 for secondary and tertiary level or higher, respectively) were associated with lower odds of being very satisfied with the service received.Caretakers who sought care in hospital were less likely to be very satisfied with service received than those at lower level facilities.In particular, caretakers who visited health posts and dispensaries for their sick child were 1.82 times more likely to be very satisfied with the service than those who visited hospitals (OR: 1.33; 95% CI 1.11 to 1.59 and OR: 1.82; 95% CI 1.40 to 2.38, respectively).Caretakers whose child received care in facilities with higher service readiness scores were more likely to be very satisfied.Problems with process of care were strong predictors of user satisfaction.Higher technical quality scores for sick child care increased the likelihood of being very satisfied (OR: 1.08, 95% CI 1.04 to 1.13 per 10% increase).Negative user experiences significantly decreased the odds of caretaker satisfaction.In particular, caretakers who perceived they were not given adequate explanation and perceived a problem with medication availability were 0.56 and 0.31 times less likely to be very satisfied with the service for their sick child, respectively (95% CI 0.46 to 0.67 and 0.27 to 0.35, respectively).Problems with the cost of services significantly reduced the odds of caretaker satisfaction (OR: 0.57, 95% CI 0.48 to 0.66).None of the providers' characteristics were associated with caretaker satisfaction.All country dummy variables, which served as proxies for national context, were significant.Compared with caretakers in Malawi, those in Afghanistan, DRC and Tanzania were less likely to be very satisfied with services, while those in Haiti were 1.76 times more likely to be very satisfied.
The results of the fixed country effects are presented in table 3. Tertiary or higher education was associated with satisfaction in Tanzania (OR: 0.4, 95% CI 0.2 to 0.8), Afghanistan (OR: 0.3, 95% CI 0.1 to 1.0) and DRC  Open access (OR: 0.2, 95% CI 0.1 to 0.7).In DCR, some facility characteristics appeared to be important determinants of satisfaction.More specifically, caregivers in health centres or private for-profit facilities had higher odds of being very satisfied compared with those seeking care in hospitals or public facilities (OR: 2.2, 95% CI 1.3 to 3.8; OR: 2.8, 95% CI 1.2 to 6.2, respectively).On the other hand, in DRC some aspects of the patients' experiences, such as wait time (OR: 0.5, 95% CI 0.3 to 1.0) and how staff treated patients (OR: 0.8, 95% CI 0.8 0.3 to 2.1) were not associated with caretaker satisfaction.Caregivers who had problems with how the staff treated them had lower odds of being very satisfied in Afghanistan, Haiti and Malawi.In all five countries, caregivers who encountered problems with medication availability and cost of services were significantly less likely to be very satisfied (see table 3).

DISCUSSION
Based on combined data from five countries, we found that factors related to the process of care during consultations for children under the age of 5 explained the highest proportion of variance in caretaker satisfaction (13.8 %), followed by factors related to the health systems' foundations (3.8%).Patient and caretakers' characteristics explained the smallest proportion of variance in caretaker satisfaction (0.9%).The children's number of symptoms and the caregiver's higher education levels both decreased the odds of being very satisfaction.The facility type and the readiness to provide sick child services also predicted overall satisfaction, although the providers' characteristics did not.In terms of process of care, the odds of being very satisfied were lower for caretakers who were not given adequate explanations and those who had encountered problems with medication availability and the cost of services.
To our knowledge, this is the first multicountry study to examine factors affecting variation in caretaker satisfaction with sick child consultations in multiple LMICs.Several findings deserve attention.First and foremost, in both the pooled and country-stratified analyses, userreported problems with process of care accounted for the largest proportion of variance explained in caretaker satisfaction with sick child care.This finding is consistent with two previous studies.In Peru, Leslie et al 20 found that user experience accounted for a larger proportion of variance in all user satisfaction measures, including three and five categories of net promoter score and satisfaction level, than the proportion explained by individual, facility and contextual factors combined.Similarly, Bleich et al's Open access study 4 based on 21 European Union countries reported that all variables considered in the analyses (eg, user experience, user expectations) accounted for 17.5% of the observed variation in user satisfaction, of which 10% was explained by user experience.
Second, technical quality of care, a subdimension of process of care, was a significant predictor of caretaker satisfaction with the service.Odds of caretakers' being very satisfied with the service increased 1.08 times with every 10% increase in technical quality score-a substantial effect size if quality were 30% or 40% higher, which is conceivable given low baseline performance.However, this association was not significant in three of the five countries.The reason for this may be that, in some contexts, patients find it difficult to assess technical quality of care due to lack of medical expertise. 215][26] This should be taken into account when user satisfaction is used to assess the performance of facilities.
Third, we found substantial between-country heterogeneity.The proportion of the total variance explained by the variables was notably higher in Afghanistan (51.7 %, as opposed to 9.0%~28.6% in the other four countries).Also, the proportion of variance explained by process of care was highest in Afghanistan (increase in R squared: 36.6% in Afghanistan vs 5.8%-24.2%).Compared with other countries, the provider's courtesy and communication (eg, explanations, discussions) appeared to be particularly important aspects of caretaker satisfaction in Afghanistan.In DRC, total variance explained by the variables was only 9%, suggesting there were still more variables influencing caretaker satisfaction, which we were unable to take into account (eg, insecurity, unpaid government employees).According to Bleich et al, 4 external factors such as media coverage could influence how satisfied people are with their healthcare system.Future qualitative and mixed methods studies could be useful to explore and uncover new context-specific factors that affect variance in user satisfaction.
Factors predicting patient satisfaction also differed between countries.Experiences of problems with medication availability or cost were the only indicators related to user experience that had a marked negative association with caretaker satisfaction across all five countries.On the other hand, inability to discuss concerns with providers and problems with how staff treated patients showed significant negative association with caretaker satisfaction in only a few countries, whereas it was identified as a strong predictor of user satisfaction in earlier studies conducted on different types of maternal care in other countries.Specifically, Dzomeku found that providers' unfriendliness and ineffective communication negatively affected maternal satisfaction in Ghana. 27Similar

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Open access results were found in Lebanon and Gambia, where it was reported that women were more satisfied with services when they had the providers' attention and adequate communication with them. 28 29As such, factors linked to patient satisfaction may depend on context, which is related to various expectations, public sentiment, values or norms. 2 30 These findings can inform strategic priorities in each country aimed at enhancing patient satisfaction with sick child consultations and possibly patient retention.This study has several limitations.First, the satisfaction rates reported by caretakers were generally high, possibly due to desirability bias in participants' responses during interviews, low patient expectations and behaviours during the audits.The observation of the providers' performance during the consultation potentially biased the patient-provider interaction.Second, some potential predictors of caretaker satisfaction, such as patients' and providers' personalities and past experiences with the healthcare system, were not available from the SPA surveys and thus were not included in our analysis.Finally, because this is a cross-sectional analysis, the associations identified cannot be interpreted causally.Despite this limitation, our study has the advantage of combining multiple sources of data (facility audits, health provider interviews, exit interviews with caretakers).It is also the first multicountry analysis to examine the determinants of variation in caretaker satisfaction for sick child care in LMICs.
The study is useful to develop a research agenda.First, in our analyses, there is still a substantial proportion of unexplained variation in caretakers' satisfaction.Future research should explore new determinants of variation in patient satisfaction throughout children's care pathways.Second, the heterogeneity between countries supports the need for more studies on how cultural differences affect patient satisfaction.

CONCLUSION
This study showed that the process of care explained the largest proportion of variance in caretaker satisfaction during sick child consultations in five LMICs.Caretakers who encountered problems related to waiting time, how the staff treated them, the amount of explanation provided, medication availability and cost of services were less likely to be very satisfied.High-quality healthcare systems should be able to satisfy users, including caretakers of sick children.People who are satisfied may have more confidence in their healthcare system and be more likely to seek care.In this regard, it is important to understand which factors shape variation in user satisfaction in different settings.Interventions targeting patient experience may be effective to improve patient satisfaction, thereby positively influencing utilisation rates and patient retention over the course of care.

Figure 1
Figure 1 Conceptual framework.Adapted from Kruk et al 1

Figure 2
Figure 2 Variance explained with addition of variables to the model.DRC, Democratic Republic of the Congo.NA, not applicable

Figure 3
Figure 3 Determinants of caretaker satisfaction.DRC, Democratic Republic of the Congo.

Table 1
Context of study countries *Data from 2019.†Data from 2020.‡Data from the most recent year available.§Percentage of people aged 15 and above able to read and write simple statements about everyday life.¶Data from 2017.DRC, Democratic Republic of the Congo.

Table 3
Final multilevel models for each country